The present embodiments relate to modeling lung cancer survival after or side-effects from therapy.
Survival or survivability from lung cancer, such as non-small cell lung cancer (NSCLC), is relatively low as compared to some other cancers. One common treatment is surgery to resect tumors. Accordingly, various prognosis techniques are directed to patients to be treated with surgery. However, these techniques may not apply to lung cancer patients treated with radiation and/or chemotherapy.
Patients with stage I-IIIB lung cancer may be treated with curative intent without surgery. Currently, prediction of survival outcome for NSCLC patients treated with (chemo) radiotherapy is mainly based on clinical factors using TNM staging. However, clinical TNM staging may be inaccurate for survival prediction of non-surgical patients, and alternatives are currently lacking.
To improve risk stratification for non-surgical patients, a number of variables associated with survival have been identified. At present, the generally accepted prognostic factors for survival of inoperable patients are performance status, weight loss, presence of comorbidity, use of chemotherapy in addition to radiotherapy, and tumor size. Retrospective studies suggest that a higher radiation dose leads to improved local control and better survival rates. For other factors, such as sex and age, the literature shows inconsistent results, making it impossible to draw definitive conclusions.
In addition to difficulties predicting survivability, there are difficulties predicting side-effects from radiation. If radiation therapy is used to treat tumors in and around the thoracic region, such as lung and breast cancer, a commonly found side-effect is radiation-induced lung injury (RILI). Toxicity (i.e., RILI) of the respiratory system may result in significant morbidity, occurring in around 13% to 37% of patients with lung cancer. To predict of the risk of RILI in non-small cell lung cancer patients, dosimetric parameters, such as the mean lung dose (MLD) or volume of the lung receiving more than 20 Gy (V20), are used. However, the accuracy of dosimetric parameters is ususally low, resulting in AUC's of about 0.60.
Imaging may be used to assist in diagnosis or prognosis. For example, the volume of a tumor is used to predict survivability. Imaging may provide other general information used by medical professionals. For example, standardized uptake values (SUV) of an imaging agent may be used to measure inflammation of lung tissue.